{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import upsetplot\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_words(path):\n",
    "    input_file = open(path, encoding='UTF-8')\n",
    "    stop_words = input_file.readlines()\n",
    "    input_file.close()\n",
    "    stop_words = list(map(lambda x:x.strip(), stop_words))\n",
    "    # only keep English words\n",
    "    #stop_words = list(map(lambda x:re.sub(\"[^a-z]+\", \"\", x), stop_words))\n",
    "    stop_words = list(filter(lambda x:len(x) > 0, stop_words))\n",
    "    # there are some duplicate stop words\n",
    "    stop_words = list(set(stop_words))\n",
    "    return stop_words\n",
    "\n",
    "def plot_result(queries, output_path = None):\n",
    "    DIR = \"stopwords/en/\"\n",
    "    result = {}\n",
    "    for stop_word_file in os.listdir(DIR):\n",
    "        # _none.txt doesn't contain any stop word\n",
    "        if stop_word_file == \"_none.txt\":\n",
    "            continue\n",
    "        # these files contain ngrams, not just single words\n",
    "        if stop_word_file in [\"galago_structured.txt\", \"gilner_morales.txt\"]:\n",
    "            continue\n",
    "        # This is meant to augment another list, and so is confusing here\n",
    "        if stop_word_file == \"galago_forumstop.txt\":\n",
    "            continue\n",
    "        words = set(get_words(os.path.join(DIR, stop_word_file)))\n",
    "        result[stop_word_file[:-4]] = {q: q in words for q in queries}   \n",
    "    result = pd.DataFrame(result).transpose()\n",
    "\n",
    "    aggregates = result.astype(bool).reset_index().groupby(queries[::-1]).count()\n",
    "    upsetplot.plot(aggregates['index'], sort_sets_by=None,\n",
    "                   sort_by='cardinality', intersection_plot_elements=4)\n",
    "    if output_path is None:\n",
    "        plt.show()\n",
    "    else:\n",
    "        plt.savefig(output_path, dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda2\\envs\\py35\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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/SIZlTconAicYxD0a8PbQ0vjVOZ6xFc7f3qvDCT68EEyWO07s1YHQHqZlDwK8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\nhKH/k7sbzwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 462.875x320 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "queries = [\"does\", \"doesn\", \"doesn't\", \"doesnt\", \"n't\", \"not\"]\n",
    "plot_result(queries, \"figures/does-upset.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda2\\envs\\py35\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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gxOZ8/B4a5caYYmAh/vnxbGPM+6E2zwENx2qcH/r7U9y+NLFyudDqcqHMpa3L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\n",
      "text/plain": [
       "<Figure size 483.5x320 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "queries = [\"do\", \"don\", \"don't\", \"dont\", \"n't\", \"not\"]\n",
    "plot_result(queries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda2\\envs\\py35\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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QWVlJTU1NW4CnpKS09TklJdq0M12rra2lqqqKxsb997HIzMwkLy+P9HTbaV/2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\nhBA+EopCCOEjoSiEED7/H9b9Xy+Xg8UrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 392.875x320 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "queries = [\"has\", \"hasn\", \"hasn't\", \"hasnt\", \"n't\", \"not\"]\n",
    "plot_result(queries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda2\\envs\\py35\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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z3bKLVfQS+T+uW5ehUMjq/4RCIcrKypxiV1dXt7ny1quqqnIu8mVlZVbHa0tL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\n0SsdkgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 399.625x320 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "queries = [\"have\", \"haven\", \"haven't\", \"havent\", \"n't\", \"not\"]\n",
    "plot_result(queries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda2\\envs\\py35\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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b9/3CpHY6iglayC4cD+xpYXey7/v/5aj9PUs7m3PdhogMB6ZbmO4CTHXRJohp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\nIAhp/H+5MK4JkuKo+QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 558.875x512 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "queries = [\"do\", \"don\", \"don't\", \"dont\", \"does\", \"doesn\", \"doesn't\", \"doesnt\", \"did\", \"didn\", \"didnt\", \"didn't\"]\n",
    "plot_result(queries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda2\\envs\\py35\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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F7Csib4rIjZk67LrueOBon+anxwsCv3wZr0Dwg21SOdOn3Yi4H76Ifz+/t9U7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\ns6bNVAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 495.625x512 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "queries = [\"has\", \"hasn\", \"hasn't\", \"hasnt\", \"have\", \"haven\", \"haven't\", \"havent\", \"had\", \"hadn\", \"hadn't\", \"hadnt\"]\n",
    "plot_result(queries, \"figures/have-upset.png\")"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:py35]",
   "language": "python",
   "name": "conda-env-py35-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
